scholarly journals Structuring of Abstract Working Memory Content by Fronto-parietal Synchrony in Primate Cortex

Neuron ◽  
2018 ◽  
Vol 99 (3) ◽  
pp. 588-597.e5 ◽  
Author(s):  
Simon Nikolas Jacob ◽  
Daniel Hähnke ◽  
Andreas Nieder
Keyword(s):  
Working Memory ◽  
Memory Content

scholarly journals Fronto-medial theta coordinates posterior maintenance of working memory content

2021 ◽  
Author(s):  
Oliver Ratcliffe ◽  
Kimron Shapiro ◽  
Bernhard P. Staresina
Keyword(s):  
Working Memory ◽  
Computational Models ◽  
Medial Cortex ◽  
Duty Cycles ◽  
Machine Learning Approach ◽  
Theta Frequency ◽  
Oscillatory Power ◽  
Posterior Parietal ◽  
Memory Content ◽  
Memory Contents

AbstractHow does the human brain manage multiple bits of information to guide goal-directed behaviour? Successful working memory (WM) functioning has consistently been linked to oscillatory power in the theta frequency band (4-8 Hz) over fronto-medial cortex (fronto-medial theta, FMT). Specifically, FMT is thought to reflect the mechanism of an executive sub-system that coordinates maintenance of memory contents in posterior regions. However, direct evidence for the role of FMT in controlling specific WM content is lacking. Here we collected high-density Electroencephalography (EEG) data whilst participants engaged in load-varying WM tasks and then used multivariate decoding methods to examine WM content during the maintenance period. Higher WM load elicited a focal increase in FMT. Importantly, decoding of WM content was driven by posterior/parietal sites, which in turn showed load-induced functional theta coupling with fronto-medial cortex. Finally, we observed a significant slowing of FMT frequency with increasing WM load, consistent with the hypothesised broadening of a theta ‘duty cycle’ to accommodate additional WM items. Together these findings demonstrate that frontal theta orchestrates posterior maintenance of WM content. Moreover, the observed frequency slowing elucidates the function of FMT oscillations by specifically supporting phase-coding accounts of WM.Significance StatementHow does the brain juggle the maintenance of multiple items in working memory (WM)? Here we show that increased WM demands increase theta power (4-8 Hz) in fronto-medial cortex. Interestingly, using a machine learning approach, we found that the content held in WM could be read out not from frontal, but from posterior areas. These areas were in turn functionally coupled with fronto-medial cortex, consistent with the idea that frontal cortex orchestrates WM representations in posterior regions. Finally, we observed that holding an additional item in WM leads to significant slowing of the frontal theta rhythm, supporting computational models that postulate longer ‘duty cycles’ to accommodate additional WM demands.

scholarly journals Tracking stimulus representation across a 2-back visual working memory task

2020 ◽  
Vol 7 (8) ◽  
pp. 190228 ◽  
Author(s):  
Quan Wan ◽  
Ying Cai ◽  
Jason Samaha ◽  
Bradley R. Postle
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Memory Task ◽  
Memory Item ◽  
Neural Representation ◽  
Stimulus Representation ◽  
Representational Format ◽  
The Status ◽  
Memory Content ◽  
Default Assumption

How does the neural representation of visual working memory content vary with behavioural priority? To address this, we recorded electroencephalography (EEG) while subjects performed a continuous-performance 2-back working memory task with oriented-grating stimuli. We tracked the transition of the neural representation of an item ( n ) from its initial encoding, to the status of ‘unprioritized memory item' (UMI), and back to ‘prioritized memory item', with multivariate inverted encoding modelling. Results showed that the representational format was remapped from its initially encoded format into a distinctive ‘opposite' representational format when it became a UMI and then mapped back into its initial format when subsequently prioritized in anticipation of its comparison with item n + 2. Thus, contrary to the default assumption that the activity representing an item in working memory might simply get weaker when it is deprioritized, it may be that a process of priority-based remapping helps to protect remembered information when it is not in the focus of attention.

scholarly journals Phase-dependent amplification of working memory content and performance

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Sanne ten Oever ◽  
Peter De Weerd ◽  
Alexander T. Sack
Keyword(s):  
Working Memory ◽  
Memory Content ◽  
And Performance

scholarly journals Selective updating of working memory content modulates meso-cortico-striatal activity

NeuroImage ◽  
2011 ◽  
Vol 57 (3) ◽  
pp. 1264-1272 ◽  
Author(s):  
Vishnu P. Murty ◽  
Fabio Sambataro ◽  
Eugenia Radulescu ◽  
Mario Altamura ◽  
Jennifer Iudicello ◽  
...  
Keyword(s):  
Working Memory ◽  
Memory Content

scholarly journals Shielding working-memory representations from temporally predictable external interference

2021 ◽  
Author(s):  
Daniela Gresch ◽  
Sage Boettcher ◽  
Freek van Ede ◽  
Anna C. Nobre
Keyword(s):  
Working Memory ◽  
Memory Performance ◽  
Memory Task ◽  
Memory Retention ◽  
Protective Effects ◽  
External Interference ◽  
Irrelevant Distractors ◽  
Temporal Predictability ◽  
Memory Representations ◽  
Memory Content

Protecting working-memory content from distracting external sensory inputs and intervening tasks is a ubiquitous demand in daily life. Here, we ask whether and how temporal expectations about external events can help mitigate effects of such interference during working-memory retention. We manipulated the temporal predictability of interfering items that occurred during the retention period of a visual working-memory task and report that temporal expectations reduce the detrimental influence of external interference on subsequent memory performance. Moreover, to determine if the protective effects of temporal expectations rely mainly on distractor suppression or also involve shielding of internal representations, we compared effects after irrelevant distractors that could be ignored vs. interrupters that required a response. Whereas distractor suppression may be sufficient to confer protection from predictable distractors, any benefits after interruption are likely to involve memory shielding. We found similar benefits of temporal expectations after both types of interference. We conclude that temporal expectations may play an important role in safeguarding behaviour based on working memory – acting, at least partly, through mechanisms that include the shielding of internal content from external interference.

scholarly journals Eye movements in real-life search are guided by task-irrelevant working-memory content

2020 ◽  
Author(s):  
Cherie Zhou ◽  
Monicque M. Lorist ◽  
Sebastiaan Mathôt
Keyword(s):  
Working Memory ◽  
Search Task ◽  
Real Life ◽  
Automatic Process ◽  
Eye Tracker ◽  
Naturalistic Environment ◽  
Memory Content ◽  
Book Covers ◽  
Open Question ◽  
Computer Tasks

AbstractAttention is automatically guided towards stimuli that match the contents of working memory. This has been studied extensively using simplified computer tasks, but it has never been investigated whether (yet often assumed that) memory-driven guidance also affects real-life search. Here we tested this open question in a naturalistic environment that closely resembles real life. In two experiments, participants wore a mobile eye-tracker, and memorized a color, prior to a search task in which they looked for a target word among book covers on a bookshelf. The memory color was irrelevant to the search task. Nevertheless, we found that participants’ gaze was strongly guided towards book covers that matched the memory color. Crucially, this memory-driven guidance was evident from the very start of the search period. These findings support that attention is guided towards working-memory content in real-world search, and that this is fast and therefore likely reflecting an automatic process.Significance statementA core concept in the field of visual working memory (VWM) is that visual attention is automatically guided towards things that resemble the content of VWM. For example, if you hold the color red in VWM, your attention and gaze would automatically be drawn towards red things in the environment. So far, studies on such memory-driven guidance have only been done with well-controlled computer tasks that used simplified search displays. Here we address the crucial and open question of whether attention is guided by the content of VWM in a naturalistic environment that closely resembles real life. To do so, we conducted two experiments with mobile eye tracking. Crucially, we found strong memory-driven guidance from the very early phase of the search, reflecting that this is a fast, and therefore likely automatic, process that also driven visual search in real life.

scholarly journals Working memory content is distorted by its use in perceptual comparisons

2020 ◽  
Author(s):  
Keisuke Fukuda ◽  
April Emily Pereira ◽  
Joseph M. Saito ◽  
Ty Yi Tang ◽  
Hiroyuki Tsubomi ◽  
...  
Keyword(s):  
Working Memory ◽  
Individual Differences ◽  
Computational Modeling ◽  
Visual Information ◽  
Dynamic Environment ◽  
Memory Bias ◽  
General Mechanism ◽  
Memory Representation ◽  
Memory Representations ◽  
Memory Content

Visual information around us is rarely static. To carry out a task in such a dynamic environment, we often have to compare current visual input with our working memory representation of the immediate past. However, little is known about what happens to a working memory (WM) representation when it is compared with perceptual input. Here, we tested university students and found that perceptual comparisons retroactively bias working memory representations toward subjectively-similar perceptual inputs. Furthermore, using computational modeling and individual differences analyses, we found that representational integration between WM representations and perceptually-similar input underlies this similarity-induced memory bias. Together, our findings highlight a novel source of WM distortion and suggest a general mechanism that determines how WM representations interact with new perceptual input.

scholarly journals Visual working memory content influences correspondence processes.

2021 ◽  
Vol 47 (3) ◽  
pp. 331-343
Author(s):  
Elisabeth Hein ◽  
Madeleine Y. Stepper ◽  
Andrew Hollingworth ◽  
Cathleen M. Moore
Keyword(s):  
Working Memory ◽  
Visual Working Memory ◽  
Memory Content

scholarly journals Flexible Working Memory Through Selective Gating and Attentional Tagging

2021 ◽  
Vol 33 (1) ◽  
pp. 1-40 ◽  
Author(s):  
Wouter Kruijne ◽  
Sander M. Bohte ◽  
Pieter R. Roelfsema ◽  
Christian N. L. Olivers
Keyword(s):  
Neural Network ◽  
Working Memory ◽  
Network Architecture ◽  
Neural Circuit ◽  
Recognition Task ◽  
Learning Rule ◽  
Task Demands ◽  
Neural Network Architecture ◽  
Complex Tasks ◽  
Memory Content

Working memory is essential: it serves to guide intelligent behavior of humans and nonhuman primates when task-relevant stimuli are no longer present to the senses. Moreover, complex tasks often require that multiple working memory representations can be flexibly and independently maintained, prioritized, and updated according to changing task demands. Thus far, neural network models of working memory have been unable to offer an integrative account of how such control mechanisms can be acquired in a biologically plausible manner. Here, we present WorkMATe, a neural network architecture that models cognitive control over working memory content and learns the appropriate control operations needed to solve complex working memory tasks. Key components of the model include a gated memory circuit that is controlled by internal actions, encoding sensory information through untrained connections, and a neural circuit that matches sensory inputs to memory content. The network is trained by means of a biologically plausible reinforcement learning rule that relies on attentional feedback and reward prediction errors to guide synaptic updates. We demonstrate that the model successfully acquires policies to solve classical working memory tasks, such as delayed recognition and delayed pro-saccade/anti-saccade tasks. In addition, the model solves much more complex tasks, including the hierarchical 12-AX task or the ABAB ordered recognition task, both of which demand an agent to independently store and updated multiple items separately in memory. Furthermore, the control strategies that the model acquires for these tasks subsequently generalize to new task contexts with novel stimuli, thus bringing symbolic production rule qualities to a neural network architecture. As such, WorkMATe provides a new solution for the neural implementation of flexible memory control.

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